Sequential Truncation of R-Vine Copula Mixture Model for High-Dimensional Datasets

Algorithm 1

Sequential truncation of the R-vine copula mixture model.

	Input: R-vine tree structures.
copula data for variables.
R-vine dimension: .
R-vine trees: .
Output: Truncated R-vine copula mixture model at level , or the full R-vine copula mixture model, if there is no possible truncation.
	fordo
Constructed mixture model by considering the tree and fitting mixture bivariate copula for each pair of variables.
Compute BIC for the mixture models (first model) and mixture model (second model).
if < then
Truncated R-vine copula mixture at level .
end if
end for